Published February 19, 2018
| Version
1.0
Dataset
Open
NFFA-EUROPE - SEM Dataset
Contributors
Related person:
Description
Dataset of 18,577 SEM images produced at CNR-IOM (Trieste, Italy). Images are classified into 10 categories in a folder structure, which have been used for convolutional neural network training. Results obtained from this dataset have been published in Modarres et al., Scientific Reports volume 7, Article number: 13282 (2017), doi:10.1038/s41598-017-13565-z
The dataset is appropriate for the purposes of this study and in general for visual object recognition software research. Any scientific metadata associated to the measure is not present in the images. The dataset is therefore relevant as a whole, being the single images entirely detached from any specific information or scientific detail related to the displayed subject. This work has been done within the NFFA-EUROPE project (www.nffa.eu) and has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 654360 NFFA-Europe.
Files
Files
(12.1 GB)
| Name | Size | Download all |
|---|---|---|
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Checksum: md5:ce5046278910173d1e8e306b0e9a7a1f
PID: http://hdl.handle.net/11304/5181815b-3b7e-43d6-b751-f1fc23dd1f46 |
700.3 MB | Download |
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Checksum: md5:0211692e2720138370226e5b5b971967
PID: http://hdl.handle.net/11304/6c6e83bc-0c13-4917-bcc2-0d744b816571 |
83.7 MB | Download |
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Checksum: md5:7cadca65719817ec3f79753436fce23e
PID: http://hdl.handle.net/11304/2cd52a61-3d45-44af-aa4e-327e1a1adc46 |
198.0 MB | Download |
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Checksum: md5:de7ec1e570382f24c80edd72d190445b
PID: http://hdl.handle.net/11304/54432c35-87dd-407a-9194-794bdc6c419f |
3.1 GB | Download |
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Checksum: md5:52a83fe8a66105b5a49b418cfc8c5c6e
PID: http://hdl.handle.net/11304/4e26bb0a-31e7-46e0-98a5-f8efbad29268 |
2.1 GB | Download |
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Checksum: md5:a7bfb3a83f0e5849a4616ee379df9762
PID: http://hdl.handle.net/11304/43d452ab-6ec8-4c39-8281-6a5ada6af653 |
2.3 GB | Download |
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Checksum: md5:6a10fa0fef72699e839e68fd6fd3b7d7
PID: http://hdl.handle.net/11304/b5e09058-3a69-4371-bf12-28c8bebf0dc6 |
2.0 GB | Download |
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Checksum: md5:0ec984f105d030cf0dad29191c470d59
PID: http://hdl.handle.net/11304/674b6f90-c22e-4335-89d3-70e240910057 |
118.8 MB | Download |
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Checksum: md5:9d2f47069f3bd7926b731472e4be6007
PID: http://hdl.handle.net/11304/f6bcd424-2688-4ccf-b88c-79c425174c0d |
855.6 MB | Download |
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Checksum: md5:cb2ad93fb5052513eafe54fcd38bcf8d
PID: http://hdl.handle.net/11304/a31815b7-5954-4b69-ba7d-913431851bea |
677.1 MB | Download |
Additional details
Identifiers
- b2rec
- 0c4df0303b6a41c3bdb17b66bdbdb39b
- b2rec
- 19cc2afd23e34b92b36a1dfd0113a89f